Optimization of a closed-loop gas system for operation of resistive plate chambers at the Large Hadron Collider

Abstract

Resistive plate chambers (RPCs), thanks to their fast time resolution (~1 ns), suitable space resolution (~1 cm) and low production cost (~25 E/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), are widely employed for the muon trigger systems at the Large Hadron Collider (LHC). Their large detector volume (they are covering a surface of about 4000 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> equivalent to 16 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> of gas volume both in ATLAS and CMS) and the use of a relatively expensive Freon-based gas mixture make a closed-loop gas circulation unavoidable. It has been observed that the return gas of RPCs operated in conditions similar to the difficult experimental background conditions at LHC contains a large amount of impurities potentially dangerous for long-term operation. Several gas-cleaning agents are currently in use in order to avoid accumulation of impurities in the closed-loop circuits. We present the results of a systematic study characterizing each of those cleaning agents. During the test, several RPCs were operated at the CERN Gamma Irradiation Facility (GIF) in a high radiation environment in order to observe the production of typical impurities: mainly fluoride ions, molecules of the Freon group and hydrocarbons. The polluted return gas was sent to several cartridges each containing a different cleaning agent. The effectiveness of each material was studied using gas chromatography and mass-spectrometry techniques. Results of this test have revealed an optimized configuration of filters that is now under long-term validation. The gas optimization studies are complemented with a finite element simulation of the gas flow distribution in the RPCs, aiming at its eventual optimization in terms of distribution and flow rate.